End of training

README.md

@@ -2,12 +2,12 @@
 language:
 - ko
 license: apache-2.0
+base_model: openai/whisper-base
 tags:
 - hf-asr-leaderboard
 - generated_from_trainer
 datasets:
 - test
-base_model: openai/whisper-base
 model-index:
 - name: basetrained
   results: []
@@ -19,9 +19,6 @@ should probably proofread and complete it, then remove this comment. -->
 # basetrained
 
 This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the test dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0000
-- Cer: 100.0
 
 ## Model description
 
@@ -41,22 +38,17 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 16
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 3000
+- num_epochs: 3.0
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Cer       |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|
-| 0.0           | 6.8   | 1000 | 0.0000          | 6107.8498 |
-| 0.0           | 13.61 | 2000 | 0.0000          | 100.0     |
-| 0.0           | 20.41 | 3000 | 0.0000          | 100.0     |
 
 
 ### Framework versions

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "openai/whisper-base",
+  "_name_or_path": "gingercake01/repo001",
   "activation_dropout": 0.0,
   "activation_function": "gelu",
   "apply_spec_augment": false,

model.safetensors

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training_args.bin

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